55 resultados para Fire severity


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In this paper we present some work concerned with the development and testing of a simple solid fuel combustion model incorporated within a Computational Fluid Dynamics (CFD) framework. The model is intended for use in engineering applications of fire field modeling and represents an extension of this technique to situations involving the combustion of solid fuels. The CFD model is coupled with a simple thermal pyrolysis model for combustible solid noncharring fuels, a six-flux radiation model and an eddy-dissipation model for gaseous combustion. The model is then used to simulate a series of small-scale room fire experiments in which the target solid fuel is polymethylmethacrylate. The numerical predictions produced by this coupled model are found to be in very good agreement with experimental data. Furthermore, numerical predictions of the relationship between the air entrained into the fire compartment and the ventilation factor produce a characteristic linear correlation with constant of proportionality 0.38 kg/sm5/12. The simulation results also suggest that the model is capable of predicting the onset of "flashover" type behavior within the fire compartment.

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This paper describes the architecture of the case based reasoning (CBR) component of Smartfire, a fire field modelling tool for use by members of the Fire Safety Engineering community who are not expert in modelling techniques. The CBR system captures the qualitative reasoning of an experienced modeller in the assessment of room geometries so as to set up the important initial parameters of the problem. The system relies on two important reasoning principles obtained from the expert: 1) there is a natural hierarchical retrieval mechanism which may be employed; and 2) much of the reasoning on a qualitative level is linear in nature, although the computational solution of the problem is non-linear. The paper describes the qualitative representation of geometric room information on which the system is based, and the principles on which the CBR system operates.

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When evacuating through fire environments, the presence of smoke may not only have a physiological impact on the evacuees but may also lead occupants to adapt their evacuation strategy through the adoption of another exit. This paper attempts to introduce this type of adaptive behaviour within the buildingEXODUS evacuation model through enabling occupants to make decisions concerning the selection of the most viable available exit during an evacuation involving fire. The development of this adaptive behaviour requires the introduction of several new capabilities namely, the representation of the occupants’ familiarity with the structure, the behaviour of an occupant that is engulfed in smoke and the behaviour of an occupant that is faced with a smoke barrier. The appropriateness of the redirection decision is dependent upon behavioural data gathered from real fire incidents (in the UK and USA) that is used to construct the redirection probabilities. The implementation is shown to provide a more complex and arguably more realistic representation of this behaviour than that provided previously.

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Numerical predictions produced by the SMARTFIRE fire field model are compared with experimental data. The predictions consist of gas temperatures at several locations within the compartment over a 60 min period. The test fire, produced by a burning wood crib attained a maximum heat release rate of approximately 11MW. The fire is intended to represent a nonspreading fire (i.e. single fuel source) in a moderately sized ventilated room. The experimental data formed part of the CIB Round Robin test series. Two simulations are produced, one involving a relatively coarse mesh and the other with a finer mesh. While the SMARTFIRE simulations made use of a simple volumetric heat release rate model, both simulations were found capable of reproducing the overall qualitative results. Both simulations tended to overpredict the measured temperatures. However, the finer mesh simulation was better able to reproduce the qualitative features of the experimental data. The maximum recorded experimental temperature (12141C after 39 min) was over-predicted in the fine mesh simulation by 12%. (C) 2001 Elsevier Science Ltd. All rights reserved.

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SMARTFIRE, an open architecture integrated CFD code and knowledge based system attempts to make fire field modeling accessible to non-experts in Computational Fluid Dynamics (CFD) such as fire fighters, architects and fire safety engineers. This is achieved by embedding expert knowledge into CFD software. This enables the 'black-art' associated with the CFD analysis such as selection of solvers, relaxation parameters, convergence criteria, time steps, grid and boundary condition specification to be guided by expert advice from the software. The user is however given the option of overriding these decisions, thus retaining ultimate control. SMARTFIRE also makes use of recent developments in CFD technology such as unstructured meshes and group solvers in order to make the CFD analysis more efficient. This paper describes the incorporation within SMARTFIRE of the expert fire modeling knowledge required for automatic problem setup and mesh generation as well as the concept and use of group solvers for automatic and manual dynamic control of the CFD code.

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The FIRE Detection and Suppression Simulation (FIREDASS) project was concerned with the development of water misting systems as a possible replacement for halon based fire suppression systems currently used in aircraft cargo holds and ship engine rooms. As part of this program of work, a computational model was developed to assist engineers optimize the design of water mist suppression systems. The model is based on Computational Fluid Dynamics (CFD) and comprised of the following components: fire model; mist model; two-phase radiation model; suppression model; detector/activation model. In this paper the FIREDASS software package is described and the theory behind the fire and radiation sub-models is detailed. The fire model uses prescribed release rates for heat and gaseous combustion products to represent the fire load. Typical release rates have been determined through experimentation. The radiation model is a six-flux model coupled to the gas (and mist) phase. As part of the FIREDASS project, a detailed series of fire experiments were conducted in order to validate the fire model. Model predictions are compared with data from these experiments and good agreement is found.

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This paper describes the architecture of the knowledge based system (KBS) component of Smartfire, a fire field modelling tool for use by members of the fire safety engineering community who are not expert in modelling techniques. The KBS captures the qualitative reasoning of an experienced modeller in the assessment of room geometries, so as to set up the important initial parameters of the problem. Fire modelling expertise is an example of geometric and spatial reasoning, which raises representational problems. The approach taken in this project is a qualitative representation of geometric room information based on Forbus’ concept of a metric diagram. This takes the form of a coarse grid, partitioning the domain in each of the three spatial dimensions. Inference over the representation is performed using a case-based reasoning (CBR) component. The CBR component stores example partitions with key set-up parameters; this paper concentrates on the key parameter of grid cell distribution.

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Fire and evacuation models with features such as the ability to realistically simulate the spread of heat and smoke and the human response to fire as well as the capability to model human performance in heeled orientations linked to a virtual reality environment that produces realistic visualisation of the modelled scenarios are now available and can be used to aid the engineer in assessing ship design and procedures. This paper describes the maritimeEXODUS ship evacuation and the SMARTFIRE fire simulation model and provides an example application demonstrating the use of the models used in pperforming fire and evacuation analysis for a large passenger ship partially based on the requirements of MSC circular 1033.

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When designing a new passenger ship or modifying an existing design, how do we ensure that the proposed design and crew emergency procedures are safe from an evacuation resulting from fire or other incident? In the wake of major maritime disasters such as the Scandinavian Star, Herald of Free Enterprise, Estonia and in light of the growth in the number of high density, high-speed ferries and large capacity cruise ships, issues concerning the evacuation of passengers and crew at sea are receiving renewed interest. Fire and evacuation models with features such as the ability to realistically simulate the spread of heat and smoke and the human response to fire as well as the capability to model human performance in heeled orientations linked to a virtual reality environment that produces realistic visualisations of the modelled scenarios are now available and can be used to aid the engineer in assessing ship design and procedures. This paper describes the maritimeEXODUS ship evacuation and the SMARTFIRE fire simulation model and provides an example application demonstrating the use of the models in performing fire and evacuation analysis for a large passenger ship partially based on the requirements of MSC circular 1033